Improving Content-Aware Video Streaming in Congested Networks with In-Network Computing
This addresses video streaming quality issues for users in congested networks, but it is incremental as it builds on existing in-network computing approaches.
The paper tackled the problem of network congestion and packet loss in video streaming by proposing an in-network computing solution with a packet drop algorithm and hardware module, resulting in over 80% reduction in intra-predicted packet loss at negligible resource and performance costs.
Network congestion and packet loss pose an ever-increasing challenge to video streaming. Despite the research efforts toward making video encoding schemes resilient to lossy network conditions, forwarding devices have not considered monitoring packet content to prioritize packets and minimize the impact of packet loss on video transmission. In this work, we advocate in favor of in-network computing employing a packet drop algorithm and an in-network hardware module to devise a solution for improving content-aware video streaming in congested network. Results show that our approach can reduce intra-predicted packet loss by over 80% at negligible resource usage and performance costs.